AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fanconi anemia group I protein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9NVI1

UPID:

FANCI_HUMAN

Alternative names:

-

Alternative UPACC:

Q9NVI1; A4ZVE4; A5YMH4; A6NJZ0; Q96JN1; Q96ST0; Q9BT96

Background:

The Fanconi anemia group I protein plays a pivotal role in DNA repair mechanisms, specifically in the repair of DNA double-strand breaks and interstrand DNA cross-links. It achieves this by facilitating FANCD2 monoubiquitination and recruitment to DNA repair sites, essential for chromosomal stability. This protein uniquely binds to both single-stranded and double-stranded DNA, highlighting its critical function in maintaining genomic integrity.

Therapeutic significance:

Fanconi anemia complementation group I, a disorder linked to mutations in the gene encoding this protein, underscores its therapeutic significance. The disease's hallmark features include bone marrow failure, congenital abnormalities, and a heightened cancer risk, attributed to defective DNA repair and chromosomal instability. Understanding the role of Fanconi anemia group I protein could open doors to potential therapeutic strategies, offering hope for targeted treatments.

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